The compression coding schemes for image signals may include coding by means of MPEG2 (Moving Picture Experts Group 2) using DCT (Discrete Cosine Transform). This coding scheme performs motion compensation predictive coding for each block.
The DCT performs discrete cosine transform on pixels in a block, re-quantizes coefficient data obtained by this discrete cosine transform, and performs variable-length coding on this re-quantized coefficient data. As this variable-length coding, entropy coding by use of codes such as Huffman codes is employed often. The image signal undergoes orthogonal transformation to be divided into many items of frequency data from a low frequency to a high frequency.
When re-quantizing these items of divided frequency data, such a quantization finely on low frequency data having a high level of importance and coarsely on high frequency data having a low level of importance is performed, taking into account human visual properties, thereby enabling effective compression to be realized while keeping a high picture quality.
According to conventional decoding by use of DCT, quantized data for each frequency component is converted into a representative value of this code and inverse DCT (IDCT: Inverse DCT) is performed on these components, thereby obtaining reproduced data. For conversion into this representative value, a quantization step width at the time of coding is used.
As described above, coding by means of MPEG using DCT has a feature that coding is performed taking into account human visual properties, to realize high efficiency compression while keeping a high picture quality.
However, coding accompanying DCT is block-unit processing, so that as a compression ratio increases, block-shaped noise, so-called block noise (block distortion) may occur in some cases. Further, a portion such as an edge subject to a steep change in luminance may be subject to blotchy noise, that is, mosquito noise due to coarse quantization of a high-frequency component.
It is conceivable that the coding noise such as block noise and mosquito noise can be removed by adaptation processing for class classification. That is, by defining an image signal containing coding noise as a first image signal and a coding noise-free image signal as a second image signal, a class to which pixel data of a target position in the second image signal belongs is detected so that in accordance with this class, the pixel data of the target position in the second image signal may be generated.
In this case, based on the first image signal, plural items of pixel data not only located in a space directional periphery with respect to the target position in the second image signal but also located in a time directional periphery thereof are selected and using these plural items of pixel data, the pixel data of the target position in the second image signal is generated, thereby enabling a quality of the second image signal to be enhanced. In this case, however, as the plural items of pixel data located in the time directional periphery, such data as to have high correlation with the plural items of pixel data located in the space directional periphery with respect to the target position needs to be selected and used.